Distributed Sensor Data Analysis for Trip Mode and User Role Inference
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Solution Overview
Problem
Processing large datasets of remotely captured sensor data poses challenges in terms of resource efficiency and effective analysis, particularly in determining trip modes and user roles during vehicle trips.
Innovation Solution
A distributed data processing system that receives and analyzes sensor data from mobile devices using various modules to detect trip characteristics, such as vehicle mode and user roles, and generates relevant trip records and user data for storage and further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a system is deployed to process large datasets of sensor data, then processing capability is improved, but resource efficiency deteriorates
Solution Approach 1:
The system segments processing tasks by deploying edge computing nodes in mobile devices that perform preliminary data processing and filtering before transmitting results to central servers. This division allows local handling of routine operations while maintaining centralized processing for complex analysis, improving overall resource efficiency.
Solution Approach 2:
The system performs preliminary data processing, filtering, and feature extraction at the edge devices before data transmission. By pre-processing sensor data locally and only transmitting essential information or aggregated results, the system reduces network bandwidth consumption and server processing loads, thereby improving resource efficiency.
2Measurement precision
If more computing resources are allocated for data processing, then analysis accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments computational tasks across multiple levels: simple filtering and feature detection are performed by mobile device sensors and edge computing nodes, while more complex pattern recognition and analysis are distributed to server-side processing units. This segmentation maintains high analysis accuracy without concentrating all complexity in a single system.
Solution Approach 2:
The system employs multi-functional processing modules that can operate at different levels of complexity depending on requirements. The same edge computing framework can handle both simple motion detection and complex trip pattern analysis, reducing overall system complexity through standardized, versatile components.
3Speed
If sensor data is processed in real-time, then responsiveness is improved, but network bandwidth consumption increases
Solution Approach 1:
The system performs preliminary processing and filtering of sensor data at edge devices, converting raw high-volume sensor streams into compact, processed information before transmission. This pre-processing maintains real-time responsiveness for local applications while dramatically reducing network bandwidth consumption for data transmission.
Solution Approach 2:
The system extracts only the essential features and aggregated results from sensor data streams before transmission, leaving detailed raw data processing to local edge devices. This extraction approach enables real-time local responsiveness while minimizing network bandwidth consumption by transmitting only necessary information.
Data Source
AI summary
Aspects of the disclosure relate to processing remotely captured sensor data. A computing platform having at least one processor, a communication interface, and memory may receive, via the communication interface, from a user computing device, sensor data captured by the user computing device using one or more sensors built into the user computing device. Subsequently, the computing platform may analyze the sensor data received from the user computing device by executing one or more data processing modules. Then, the computing platform may generate trip record data based on analyzing the sensor data received from the user computing device and may store the trip record data in a trip record database. In addition, the computing platform may generate user record data based on analyzing the sensor data received from the user computing device and may store the user record data in a user record database.